{"id":"W4405797009","doi":"10.1158/2767-9764.crc-24-0287","title":"Clinical Proteomics Reveals Vulnerabilities in Noninvasive Breast Ductal Carcinoma and Drives Personalized Treatment Strategies","year":2024,"lang":"en","type":"article","venue":"Cancer Research Communications","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; University of Manitoba; IGNIS Innovation (Canada); Jewish General Hospital; Research Institute in Oncology and Hematology; McGill University; CancerCare Manitoba","funders":"National Cancer Institute; Warren Y. Soper Charitable Trust; Fondation De Famille Alvin Segal; Jewish General Hospital; Fondation du cancer du sein du Québec; Genome Canada; Faculty of Medicine, McGill University; McGill University","keywords":"Druggability; Proteomics; Breast cancer; Ductal carcinoma; PI3K/AKT/mTOR pathway; Biology; Quantitative proteomics; Cancer; Bioinformatics; Cancer research; Medicine; Computational biology; Oncology; Pathology; Internal medicine; Gene; Signal transduction; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001116959,0.000522076,0.0004346666,0.0008130342,0.0002412567,0.001257529,0.000246265,0.0005748544,0.001344493],"category_scores_gemma":[0.001223179,0.000193039,0.0002271092,0.000645239,0.0003924103,0.0005527099,0.0006037169,0.0005791959,0.0005108499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004351761,"about_ca_system_score_gemma":0.0004321136,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002708102,"about_ca_topic_score_gemma":0.0004548795,"domain_scores_codex":[0.9995771,0.00009489054,0.00003167732,0.0001224045,0.0001201511,0.00005384061],"domain_scores_gemma":[0.9995733,0.00010004,0.0001553692,0.00004387307,0.00007767789,0.00004968815],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001297466,0.0003195002,0.2472085,0.0006763147,0.0002758877,0.0006226832,0.0002465694,0.002340976,0.6406668,0.001215103,0.002550154,0.1025801],"study_design_scores_gemma":[0.00008667571,0.001318722,0.6272129,0.000188775,0.0004313154,0.004383751,0.0008131124,0.01857642,0.3254688,0.00724959,0.01419049,0.0000794191],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.977084,0.006483295,0.01020844,0.001561672,0.00004962758,0.00008134278,0.001261794,0.0001945216,0.003075381],"genre_scores_gemma":[0.991179,0.001839765,0.005315823,0.0004641957,0.00003778706,0.00003372232,0.0004779697,0.00002232603,0.0006293851],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001344493,"threshold_uncertainty_score":0.005907118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1277857034909281,"score_gpt":0.4749458926351294,"score_spread":0.3471601891442013,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}